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Effective postoperative analgesia is critical for patient recovery, satisfaction, and the reduction of hospital stay duration. Continuous peripheral nerve blocks (CPNB) via catheter placement represent a cornerstone in achieving these objectives. Traditionally, follow-up for these patients has relied on standardized telephone protocols conducted by trained personnel. Original previous research in 2024 demonstrated that an automated text-messaging platform was feasible and maintained high patient satisfaction, it resulted in a significantly higher rate of unscheduled patient-initiated inquiries (28.3% vs. 6.4%) compared to traditional phone calls, likely due to a lack of adaptive response capabilities.
Objective: This study aims to evaluate an enhanced technological iteration of our follow-up platform. By integrating an Artificial Intelligence (AI) interface trained on specialized clinical protocols, the new system is designed to provide automated, personalized and adaptive recommendations to patients.
Methods and Intervention: The study will compare the effectiveness of this AI-driven platform against the previous version of the non-adaptive automated messaging system. The primary outcome is to compare the number of patient-initiated inquiries (re-consultations). Secondary outcomes include patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three.
Impact: The investigators hypothesize that the integration of AI will optimize human resources and improve patient autonomy without compromising safety or satisfaction, ultimately providing a scalable model for postoperative regional analgesia monitoring.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| AI-App | Experimental | Artificial Intelligence-driven application |
|
| Control-App | Active Comparator | Standard automated messaging application |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI-driven follow-up platform | Other | The study will compare the effectiveness of this AI-driven platform against the previous version of the non-adaptive automated messaging system. The primary outcome is to compare the number of patient-initiated inquiries (re-consultations). Secondary outcomes include patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three. |
| Measure | Description | Time Frame |
|---|---|---|
| Comparison of patient-initiated inquiry rates between AI-App and Control-App | Comparison of patient-initiated inquiry rates between the Artificial Intelligence-driven application (AI-App) and the standard automated messaging application (Control-App) during ambulatory postoperative follow-up. | From registration to the end of the 3-day outpatient postoperative follow-up |
| Measure | Description | Time Frame |
|---|---|---|
| Engage with the AI-driven app | Proportion of patients who successfully engage with the AI-driven application. This includes a cumulative analysis over the 3-day follow-up period and a granular day-to-day response analysis. | From registration to the end of the 3-day outpatient postoperative follow-up |
| Assessment patient satisfaction |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Felipe Yañez Herrera | Contact | +56988129267 | feliyanezherrera@gmail.com | |
| Pontificia Universidad Catolica de Chile | Contact |
| Name | Affiliation | Role |
|---|---|---|
| Felipe Yañez Herrera | Pontificia Universidad Catolica de Chile | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Region Metropolitana de Chile | Santiago | Chile |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 25679749 | Background | Semple JL, Sharpe S, Murnaghan ML, Theodoropoulos J, Metcalfe KA. Using a mobile app for monitoring post-operative quality of recovery of patients at home: a feasibility study. JMIR Mhealth Uhealth. 2015 Feb 12;3(1):e18. doi: 10.2196/mhealth.3929. | |
| 34226197 | Background | Pai B H P, Lai YH. Regional anesthesia and pain medicine. Reg Anesth Pain Med. 2022 Feb;47(2):144-145. doi: 10.1136/rapm-2021-102939. Epub 2021 Jul 5. No abstract available. |
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Interventional, prospective, randomized clinical trial.
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|
| Satisfaction | Other | Register patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three |
|
| Adherence to the follow-up protocol | Other | Register patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three |
|
| Response rates from postoperative days one through three | Other | Register patient satisfaction, adherence to the follow-up protocol, and response rates from postoperative days one through three |
|
Assessment and comparison of patient satisfaction scores between the AI-driven application group and the traditional telephone follow-up group, utilizing a standardized satisfaction scale survey in Spanish "Questionnaire of Satisfaction and Perceived Quality in Hospital Health Care of the Department of Studies and Development of the Superintendency of Health" (PQA). In this instrument, the patient was asked to respond using a five-point Likert scale. The extremes of the scale were labelled 'very poor' to 'definitely yes' depending upon the question. Patient responses to each PQA Likert scale and visual analogue questions were scored from 1 to 5. The performance score was defined as the proportion of patients with an unsatisfactory patient response. A quality index was calculated for each PQA question by multiplying the importance score against the performance score. |
| From registration to the end of the 3-day outpatient postoperative follow-up |
| Adherence between the Control-App and AI-App | Comparative analysis of patient adherence between the standard automated messaging application (Control-App) and the AI-driven application (AI-App). Adherence is defined as the successful completion of the response protocol during the three-day monitoring period. | From registration to the end of the 3-day outpatient postoperative follow-up |
| 34800733 | Background | Perdomo-Pantoja A, Alomari S, Lubelski D, Liu A, DeMordaunt T, Bydon A, Witham TF, Theodore N. Implementation of an Automated Text Message-Based System for Tracking Patient-Reported Outcomes in Spine Surgery: An Overview of the Concept and Our Early Experience. World Neurosurg. 2022 Feb;158:e746-e753. doi: 10.1016/j.wneu.2021.11.051. Epub 2021 Nov 17. |
| 36066936 | Background | Miller HN, Voils CI, Cronin KA, Jeanes E, Hawley J, Porter LS, Adler RR, Sharp W, Pabich S, Gavin KL, Lewis MA, Johnson HM, Yancy WS Jr, Gray KE, Shaw RJ. A Method to Deliver Automated and Tailored Intervention Content: 24-month Clinical Trial. JMIR Form Res. 2022 Sep 6;6(9):e38262. doi: 10.2196/38262. |
| 33649155 | Background | Gessner D, Hunter OO, Kou A, Mariano ER. Automated text messaging follow-up for patients who receive peripheral nerve blocks. Reg Anesth Pain Med. 2021 Jun;46(6):524-528. doi: 10.1136/rapm-2021-102472. Epub 2021 Mar 1. |
| 33410758 | Background | van der Velde M, Valkenet K, Geleijn E, Kruisselbrink M, Marsman M, Janssen LM, Ruurda JP, van der Peet DL, Aarden JJ, Veenhof C, van der Leeden M. Usability and Preliminary Effectiveness of a Preoperative mHealth App for People Undergoing Major Surgery: Pilot Randomized Controlled Trial. JMIR Mhealth Uhealth. 2021 Jan 7;9(1):e23402. doi: 10.2196/23402. |
| 30726985 | Background | Highland KB, Tran J, Edwards H, Bedocs P, Suen J, Buckenmaier CC. Feasibility of App-Based Postsurgical Assessment of Pain, Pain Impact, and Regional Anesthesia Effects: A Pilot Randomized Controlled Trial. Pain Med. 2019 Aug 1;20(8):1592-1599. doi: 10.1093/pm/pny288. |
| Background | 2. Usability Measurement of Mobile Applications with System Usability Scale (SUS) - Aycan Kaya, Reha Ozturk and Cigdem Altin Gumussoy |
| 33404791 | Background | Ooi G, Schwenk ES, Torjman MC, Berg K. A Randomized Trial of Manual Phone Calls Versus Automated Text Messages for Peripheral Nerve Block Follow-Ups. J Med Syst. 2021 Jan 4;45(1):7. doi: 10.1007/s10916-020-01699-z. |
| ID | Term |
|---|---|
| D000377 | Agnosia |
| ID | Term |
|---|---|
| D010468 | Perceptual Disorders |
| D019954 | Neurobehavioral Manifestations |
| D009461 | Neurologic Manifestations |
| D009422 | Nervous System Diseases |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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| ID | Term |
|---|---|
| D000096002 | Physician Engagement |
| ID | Term |
|---|---|
| D000074824 | Work Engagement |
| D010559 | Personnel Management |
| D009934 | Organization and Administration |
| D006298 | Health Services Administration |
| D003695 | Delivery of Health Care |
| D010346 | Patient Care Management |
| D017530 | Health Care Quality, Access, and Evaluation |
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